Chais_2026

E48 Teachers’ Perceptions of AI-Enhanced Data-Driven Decision-Making (DDDM) in Schools: A Systematic Review Mandinach, E. B., & Schildkamp, K. (2021). Misconceptions about data-based decision making in education: An exploration of the literature. Studies in Educational Evaluation, 69, 100842. https://doi.org/10.1016/j.stueduc.2020.100842 Marsh, J. A., & Farrell, C. C. (2014). How leaders can support teachers with data-driven decision making: A framework for understanding capacity building. Educational Management Administration & Leadership, 43(2), 269-289. https://doi.org/10.1177/1741143214537229 *Michos, K., Schmitz, M. L., & Petko, D. (2023). Teachers' data literacy for learning analytics: a central predictor for digital data use in upper secondary schools. Education and Information Technologies, 28(11), 14453-14471. https://doi.org/10.1007/s10639-023-11772-y *Nazaretsky, T., Ariely, M., Cukurova, M., & Alexandron, G. (2022). Teachers' trust in AI‐powered educational technology and a professional development program to improve it. British Journal of Educational Technology, 53(4), 914-931. https://doi.org/10.1111/bjet.13232 *Olaseni, V. M. (2020). Teachers' perception towards integration of artificial intelligence tutoringbased system in the school curriculum: A survey. Educational Research, 8(11B), 6263-6272. https://doi.org/10.38159/ehass.202451319 Romero, C., & Ventura, S. (2020). Educational data mining and learning analytics: An updated survey. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 10(3), e1355. https://doi.org/10.1002/widm.1355 Sajja, R., Sermet, Y., Cwiertny, D., & Demir, I. (2025). Integrating AI and learning analytics for datadriven pedagogical decisions and personalized interventions in education. Technology, Knowledge and Learning, 1-31. https://doi.org/10.1007/s10758-025-09897-9 Schildkamp, K., & Poortman, C. L. (2015). Factors influencing the functioning of data teams. Teachers College Record, 117(4), 1-42. https://doi.org/10.1177/016146811511700403 *Song, Y., Kim, J., Xing, W., Liu, Z., Li, C., & Oh, H. (2025). Elementary school students and teachers' perceptions toward creative mathematical writing with generative AI. Journal of Research on Technology in Education, 1-23. https://doi.org/10.1080/15391523.2025.2455057 *Thompson, T., St John, J., Pradhan, S., & Ottmar, E. (2025). MathFlowLens Dashboard: Co‐designing teacher orchestration tools to engage in discourse around students' mathematical strategies. Journal of Computer Assisted Learning, 41(3), e70025. https://doi.org/10.1111/jcal.70025 *Tran, N., Pierce, B., Litman, D., Correnti, R., & Matsumura, L. C. (2024). Multi-dimensional performance analysis of large language models for classroom discussion assessment. Journal of Educational Data Mining, 16(2), 304-335. https://doi.org/10.5281/zenodo.14549071 *Viberg, O., Cukurova, M., Feldman-Maggor, Y., Alexandron, G., Shirai, S., Kanemune, S., ... & Kizilcec, R. F. (2024). What explains teachers' trust in AI in education across six countries? International Journal of Artificial Intelligence in Education, 1-29. https://doi.org/10.1007/s40593-024-00433-x *Wang, J., Dudy, S., He, X., Wang, Z., Southwell, R., & Whitehill, J. (2025). Optimizing speaker diarization for the classroom: Applications in timing student speech and distinguishing teachers from children. Journal of Educational Data Mining, 17(1), 98-125. https://doi.org/10.1111/bjet.13308 *Wang, Y. (2021). When artificial intelligence meets educational leaders' data-informed decisionmaking: A cautionary tale. Studies in Educational Evaluation, 69, 100872. https://doi.org/10.1016/j.stueduc.2020.100872 *Whitehill, J., & LoCasale-Crouch, J. (2024). Automated evaluation of classroom instructional support with LLMs and BoWs: Connecting global predictions to specific feedback. Journal of Educational Data Mining. https://doi.org/10.48550/arXiv.2310.01132 Williamson, B., & Eynon, R. (2020). Historical threads, missing links, and future directions in AI in education. Learning, Media and Technology, 45(3), 223-235. https://doi.org/10.1080/17439884.2020.1798995

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